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谷歌推出史上最強(qiáng)人臉識(shí)別系統(tǒng)

谷歌推出史上最強(qiáng)人臉識(shí)別系統(tǒng)

Derrick Harris 2015年03月24日
谷歌研究人員日前聲稱,,該公司正在開發(fā)的FaceNet人工智能系統(tǒng)是迄今為止最精確的人臉識(shí)別技術(shù),。這套系統(tǒng)不僅能夠在龐大的數(shù)據(jù)庫(kù)中迅速識(shí)別兩張臉是否一樣,還能將人名和臉匹配,甚至能將那些看起來(lái)最像或最不像的臉歸集在一起,。FaceNet的橫空出世意味著“深度學(xué)習(xí)”這一人工智能技術(shù)又向前邁進(jìn)了一大步,。

????還有幾家科技創(chuàng)業(yè)公司正將深度學(xué)習(xí)技術(shù)用于實(shí)時(shí)分析醫(yī)療圖像,,并提供諸如文本分析、計(jì)算機(jī)視覺及語(yǔ)音識(shí)別這類云計(jì)算服務(wù)項(xiàng)目,。近年來(lái),,Twitter、Pinterest,,、Dropbox,、雅虎和谷歌等公司都收購(gòu)了一些專攻深度學(xué)習(xí)技術(shù)的創(chuàng)業(yè)公司。IBM公司剛剛收購(gòu)了一家位于丹佛,,名為AlchemyAPI的初創(chuàng)企業(yè),,用以提升其Watson超級(jí)計(jì)算機(jī)的智能水平,并支持其全新的Bluemix云平臺(tái)(該平臺(tái)的理念是:開發(fā)者可以方便地將移動(dòng)和網(wǎng)絡(luò)應(yīng)用與云服務(wù)連接起來(lái),,借以打造一些智能應(yīng)用,,而無(wú)需再鉆研人工智能背后復(fù)雜的計(jì)算機(jī)科學(xué))。

????不止于此,。隨著消費(fèi)級(jí)機(jī)器人,、無(wú)人駕駛汽車及智能家居逐漸成為現(xiàn)實(shí),深度學(xué)習(xí)技術(shù)也將如影隨形,,為我們這些新玩具提供耳目和一些頭腦功能,。美國(guó)國(guó)防部高級(jí)研究計(jì)劃局(DARPA)也在探索如何借助深度學(xué)習(xí)技術(shù)來(lái)實(shí)時(shí)理解龐大的情報(bào)信息流。

????我猜想,,DARPA正在關(guān)注谷歌的FaceNet系統(tǒng),,并為之激動(dòng)。(財(cái)富中文網(wǎng))

????譯者:清遠(yuǎn)

????審校:任文科

????There are also several technology startups using deep learning to analyze medical images in real time, and to provide capabilities such as text analysis, computer vision, and voice recognition as cloud computing services. Twitter, Pinterest, Dropbox, Yahoo, and Google have all acquired deep learning startups in recent years. And IBM IBM -0.08% just bought a Denver-based startup called AlchemyAPI to help make its Watson system smarter and bolster its new Bluemix cloud platform. (The idea: Developers can easily connect mobile and web applications to cloud services and therefore build smart applications without ever studying the complex computer science that underpins artificial intelligence.)

????That’s not all. As consumer robots, driverless cars and smart homes become real, deep learning will be there, too, providing the eyes, ears, and some of the brains for our new toys. DARPA, the U.S. Department of Defense’s research agency, is also investigating how deep learning techniques might be able to help it make sense of the streams of communications crossing intelligence networks everyday.

????Something tells me it’s looking at Google’s FaceNet and getting pretty excited, too.

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